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Antennas in Walls: Performance Analysis of Microstrip Patch Antennas Designed for Internet of Paint (IoP)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This study presents a simulated transceiver with a microstrip patch antenna (MPA) designed to resonate at 150 GHz and embedded in paint. The in-paint MPA (IP-MPA) is designed for the Internet of Paint (IoP) paradigm, which envisions seamless device communication through a paint layer on walls. This study introduces a comprehensive channel model for transceivers in paint at arbitrary depths and IP-MPA orientations. The best antenna orientations are analyzed for IoP channel performance. Extensive simulations indicate that the lateral waves, which propagate along the air-paint interface, exhibit the lowest loss, making this path the most reliable for communication between transceivers in paint. Furthermore, the maximum received power for each propagation path, except for the direct path, depends on depth. The findings suggest that the proposed network of IP-MPA-enabled transceivers for IoP has the potential to transform conventional walls into an integrated high-speed wireless communication and sensing infrastructure.

Original languageEnglish (US)
Title of host publicationGLOBECOM 2025 - 2025 IEEE Global Communications Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2807-2812
Number of pages6
ISBN (Electronic)9798331577810
DOIs
StatePublished - 2025
Event2025 IEEE Global Communications Conference, GLOBECOM 2025 - Taipei, Taiwan, Province of China
Duration: Dec 8 2025 → Dec 12 2025

Publication series

NameProceedings - IEEE Global Communications Conference, GLOBECOM
ISSN (Print)2334-0983
ISSN (Electronic)2576-6813

Conference

Conference2025 IEEE Global Communications Conference, GLOBECOM 2025
Country/TerritoryTaiwan, Province of China
CityTaipei
Period12/8/25 → 12/12/25

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

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